Economic Analysis: Theory and Practice
 

Forecasting the commercial bank default based on a probabilistic model

Vol. 16, Iss. 12, DECEMBER 2017

Received: 24 July 2017

Received in revised form: 14 September 2017

Accepted: 2 November 2017

Available online: 22 December 2017

Subject Heading: FINANCIAL STABILITY AND SOLVENCY

JEL Classification: G21, G33

Pages: 2376–2391

https://doi.org/10.24891/ea.16.12.2376

Yashina N.I. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation
sitnicof@mail.ru

Makarova S.D. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation
makarovasd@iee.unn.ru

Makarov I.A. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation
makartolk@mail.ru

Otdelkina A.A. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation
otdalla@gmail.com

Importance The article evaluates the efficiency of commercial banks' operations by means of econometric model for default. It represents a practical approach to assessing the probability of bankruptcy of commercial banks under modern Russian economy.
Objectives The aim of the study is to build an econometric model with a set of factors (indicators) enabling early prediction of possible default of a commercial bank based on changes within the annual period preceding the default.
Methods We apply a method of econometric modeling for default probability that rests on evaluation of commercial bank's financial stability as a baseline approach. The distinctive feature of the study is the use of multiple correlation and regression analysis of macro- and microeconomic indicators. Macroeconomic indicators help consider the impact of external factors on financial stability, and microeconomic indicators that are reported in official financial statements of commercial banks, allow for objectivity in calculations.
Results We present an econometric model to predict a possible negative scenario of commercial bank's operations based on a set of indicators that allow early prediction of default with significant degree of probability. The obtained results enable to forecast the development of possible negative processes in commercial bank's operations with 1-year time lag.
Conclusions The proposed method for early prediction of commercial banks' critical state will facilitate timely measures to strengthen their financial stability and prevent bankruptcy.

Keywords: bank, stability, modeling, default, projection

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